Longitudinal network changes and phenoconversion risk in isolated REM sleep behavior disorder

Chris C. Tang, Yoshikazu Nakano, An Vo, Nha Nguyen, Katharina A. Schindlbeck, Paul J. Mattis, Kathleen L. Poston, Jean-François Gagnon, Ronald B. Postuma, Martin Niethammer, Yilong Ma, Shichun Peng, Vijay Dhawan and David Eidelberg ()
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Chris C. Tang: The Feinstein Institutes for Medical Research
Yoshikazu Nakano: The Feinstein Institutes for Medical Research
An Vo: The Feinstein Institutes for Medical Research
Nha Nguyen: The Feinstein Institutes for Medical Research
Katharina A. Schindlbeck: The Feinstein Institutes for Medical Research
Paul J. Mattis: The Feinstein Institutes for Medical Research
Kathleen L. Poston: Stanford University School of Medicine
Jean-François Gagnon: Centre d’Études Avancées en Médecine du Sommeil, Hôpital du Sacré-Cœur de Montréal
Ronald B. Postuma: Centre d’Études Avancées en Médecine du Sommeil, Hôpital du Sacré-Cœur de Montréal
Martin Niethammer: The Feinstein Institutes for Medical Research
Yilong Ma: The Feinstein Institutes for Medical Research
Shichun Peng: The Feinstein Institutes for Medical Research
Vijay Dhawan: The Feinstein Institutes for Medical Research
David Eidelberg: The Feinstein Institutes for Medical Research

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Isolated rapid eye movement sleep behavior disorder is a prodrome of α-synucleinopathies. Using positron emission tomography, we assessed changes in Parkinson’s disease-related motor and cognitive metabolic networks and caudate/putamen dopaminergic input in a 4-year longitudinal imaging study of 13 male subjects with this disorder. We also correlated times to phenoconversion with baseline network expression in an independent validation sample. Expression values of both Parkinson’s disease-related networks increased over time while dopaminergic input gradually declined in the longitudinal cohort. While abnormal functional connections were identified at baseline in both networks, others bridging these networks appeared later. These changes resulted in compromised information flow through the networks years before phenoconversion. We noted an inverse correlation between baseline network expression and times to phenoconversion to Parkinson’s disease or dementia with Lewy bodies in the validation sample. Here, we show that the rate of network progression is a useful outcome measure in disease modification trials.

Date: 2024
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DOI: 10.1038/s41467-024-54695-z

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